ArticleEGEMS (Washington, DC)2016
A Framework to Support the Sharing and Reuse of Computable Phenotype Definitions Across Health Care Delivery and Clinical Research Applications.
Article in EGEMS (Washington, DC), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Development and evaluation of a computable phenotype to identify pediatric patients with leukemia and lymphoma treated with chemotherapy using electronic health record data.Pediatric blood & cancer · 2019Trial
- Evaluating the feasibility of the CIPHER metadata framework towards building a conceptual phenotype standard.JAMIA open · 2026Article
- Bridging Data, Semantics, and Clinical Reasoning: A Knowledge Graph Framework for Pediatric Obstructive Sleep Apnea.Children (Basel, Switzerland) · 2026Article
- Identifying Hemophagocytic Lymphohistiocytosis and Describing Outcomes Using Computable Phenotypes: Retrospective Cohort Study.JMIR cancer · 2026Article
- PhenoFit: a framework for determining computable phenotyping algorithm fitness for purpose and reuse.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Unmasking heterogeneity in type 2 diabetes: the clinical relevance of phenotyping in the era of precision medicine.Acta diabetologica · 2025Article
- Incidence of and risk factors for hospital-acquired bleeding in people with cancer: a systematic review.Research and practice in thrombosis and haemostasis · 2025Article
- Utilization of Computable Phenotypes in Electronic Health Record Research: A Review and Case Study in Atopic Dermatitis.The Journal of investigative dermatology · 2025Review
- Increasing Methodological Transparency and Openness in Rehabilitation-Related Health Services Research Using Claims Data: A Case Example.Physical therapy · 2025Article
- US public health surveillance, reimagined.Learning health systems · 2024Article
- Computable phenotype for diagnostic error: developing the data schema for application of symptom-disease pair analysis of diagnostic error (SPADE).Diagnosis (Berlin, Germany) · 2024Article
- Combining Federated Machine Learning and Qualitative Methods to Investigate Novel Pediatric Asthma Subtypes: Protocol for a Mixed Methods Study.JMIR research protocols · 2024Article
- An Online Tool for Correcting Performance Measures of Electronic Phenotyping Algorithms for Verification Bias.ACI open · 2024Article
- Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients.PloS one · 2024Article
- Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network.JAMIA open · 2023Article
- Evaluating construct validity of computable acute respiratory distress syndrome definitions in adults hospitalized with COVID-19: an electronic health records based approach.BMC pulmonary medicine · 2023Article
- Development of a computable phenotype using electronic health records for venous thromboembolism in medical inpatients: the Medical Inpatient Thrombosis and Hemostasis study.Research and practice in thrombosis and haemostasis · 2023Article
- The relative risk of bleeding after medical hospitalization: the medical inpatient thrombosis and hemorrhage study.Journal of thrombosis and haemostasis : JTH · 2023Observational
- Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration.BMC medical informatics and decision making · 2023Article
- Development and validation of algorithms to identify patients with chronic kidney disease and related chronic diseases across the Northern Territory, Australia.BMC nephrology · 2022Article
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Authors and funding
3 authors.
Funding
Abstract
introductionThe ability to reproducibly identify clinically equivalent patient populations is critical to the vision of learning health care systems that implement and evaluate evidence-based treatments. The use of common or semantically equivalent phenotype definitions across research and health care use cases will support this aim. Currently, there is no single consolidated repository for computable phenotype definitions, making it difficult to find all definitions that already exist, and also hindering the sharing of definitions between user groups.
methodDrawing from our experience in an academic medical center that supports a number of multisite research projects and quality improvement studies, we articulate a framework that will support the sharing of phenotype definitions across research and health care use cases, and highlight gaps and areas that need attention and collaborative solutions. FRAMEWORK: An infrastructure for re-using computable phenotype definitions and sharing experience across health care delivery and clinical research applications includes: access to a collection of existing phenotype definitions, information to evaluate their appropriateness for particular applications, a knowledge base of implementation guidance, supporting tools that are user-friendly and intuitive, and a willingness to use them. NEXT STEPS: We encourage prospective researchers and health administrators to re-use existing EHR-based condition definitions where appropriate and share their results with others to support a national culture of learning health care. There are a number of federally funded resources to support these activities, and research sponsors should encourage their use.
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